LeonSGP
92ada619d2
Creating a table from an Arrow `list` or `large_list` vector field infers a fixed-size vector type, but currently drops that field's metadata. Descriptions and tags such as `lancedb:description` and `lancedb:tag:model` disappear even though the input field carries them. Preserve the original field metadata while replacing its inferred type. Tests use public synchronous and asynchronous table creation, reopening, and reads for floating-point and integer inference, checking the complete schema and row values. Existing dtype inference and nullability remain unchanged. Validation on macOS arm64 with an official native extension built from main `d864e719` using Rust 1.97.0: - Python 3.11.14 and 3.13.11: full `pytest -m "not slow and not s3_test" -q -rs python/tests`: **1,533 passed, 37 skipped, 68 deselected** each, wall times 331.464 s and 416.308 s. - Added public SDK cases on unchanged main: **12 failed**; after the fix: **12 passed** on each runtime. Final installed distributions passed **8 public SDK round trips** each, including fixed-size fields and fields without metadata. - Documentation tests on Python 3.11.14: **77 passed, 6 skipped**. Ruff lint/format, Pyright (**0 errors**), applicable pre-commit hooks (**4 passed, 2 without matching files**), compile checks and `git diff --check` passed. - Comparable unchanged-main full baselines from the same day, native extension and dependency versions: **1,521 passed, 37 skipped, 68 deselected** on each runtime. These were reused rather than rerun. The final local wheel is an explicitly verified repack of the official main wheel, replacing only `table.py` and `RECORD`; all production Python files match the tested source and the native extension is unchanged. No candidate Rust rebuild was performed. Slow/S3 integration tests, the remaining OS/runtime and minimum-dependency matrices, and the workflow's Linux/Python 3.13 doctest job were not run locally. The existing Rust migration draft #2970 and issues #3216/#3222 do not fix this metadata loss in the current Python path; a future migration should preserve the same metadata. During final verification main advanced to `81d52a98` through #4373 and the beta.13 version bump. Neither modified the two files here; the local native and full-suite validation above remain explicitly based on `d864e719`, and the updated native changes have not been tested locally. AI assistance: developed and verified with **gpt-6.1-sol**.
LanceDB Python SDK
A Python library for LanceDB.
Installation
pip install lancedb
If no wheel is published for your platform, pip builds lancedb from the source distribution. That build needs a Rust toolchain and protoc (the Protocol Buffers compiler) on your PATH, and can take a while.
Pre-Haswell x86_64 hosts: lancedb-compat
The default lancedb wheel targets x86-64-haswell (AVX2 + FMA + F16C) for full performance on modern hardware. Pre-Haswell hosts — Intel Sandy Bridge / Ivy Bridge / Westmere; AMD Bulldozer / Piledriver / Steamroller — don't have AVX2 and crash with Illegal instruction at import lancedb.
For those hosts, install the lancedb-compat package instead:
pip install lancedb-compat
Same Python API (import lancedb works as usual). The compat wheel is compiled at the x86-64-v2 baseline (Nehalem-class) and uses runtime SIMD dispatch in the embedded lance crate to pick the right kernel tier (scalar / AVX / AVX+FMA / AVX2+FMA / AVX-512) at load time, so it still goes fast on modern hardware while running cleanly on the pre-Haswell silicon. Use lance.simd_info() from Python to verify which tier was selected.
lancedb and lancedb-compat install to the same lancedb/ namespace and conflict at install time. Pick one. To switch, pip uninstall lancedb first, then pip install lancedb-compat (or vice-versa).
If you need a custom baseline (or lancedb-compat isn't yet published for your platform), build from source with the override:
RUSTFLAGS="-C target-cpu=x86-64-v2" maturin build --release
pip install ./target/wheels/lancedb-*.whl
Preview Releases
Stable releases are created about every 2 weeks. For the latest features and bug fixes, you can install the preview release. These releases receive the same level of testing as stable releases, but are not guaranteed to be available for more than 6 months after they are released. Once your application is stable, we recommend switching to stable releases.
pip install --pre --extra-index-url https://pypi.fury.io/lancedb/ lancedb
Threading in CPU-limited containers
LanceDB uses separate pools for compute work and storage I/O. On a container with two visible CPUs, current releases intentionally use one compute worker by default; no manual configuration is needed. If every query logs an I/O core reservation warning on a two-CPU container, upgrade from LanceDB 0.21.1 or earlier.
The two commonly tuned environment variables control different resources:
LANCE_CPU_THREADSoverrides the number of compute workers. One worker is the appropriate setting for a two-CPU container when an explicit override is needed.LANCE_IO_THREADScontrols concurrent storage operations, not reserved CPU cores. Its default can be greater than the number of CPUs because I/O workers spend much of their time waiting for storage.
Keep the defaults unless measurements show that the workload benefits from an override. See the Lance threading model for the current defaults and tuning guidance.
Usage
Basic Example
import lancedb
db = lancedb.connect('<PATH_TO_LANCEDB_DATASET>')
table = db.open_table('my_table')
results = table.search([0.1, 0.3]).limit(20).to_list()
print(results)
Development
See CONTRIBUTING.md for information on how to contribute to LanceDB.